Deep reasoning, thinking and effort for critical tasks
You send a simple prompt to Claude, it replies in 2 seconds. You send a complex case (math, code, planning), it replies just as fast, but the output is broken. Why? It did not take the TIME to reason. On current Claude models thinking is adaptive: the model decides how much to think before answering, and your lever is the effort parameter (from low to max). This course gives you the 4 foundations: (1) when reasoning really pays off vs when it wastes, (2) how to parameterize a call (adaptive thinking, effort level, reading the thinking block and the text block), (3) the thinking + tool use combo that changes agent quality, (4) the cost/quality arbitrage to raise effort at the right moment in prod. By the end, you know how to arbitrate between speed and depth, and you build critical features (debug, planning, decision trees) you did not dare build before.
Level : intermediate